• DocumentCode
    1558099
  • Title

    Neuro-fuzzy systems for computer-aided myocardial viability assessment

  • Author

    Behloul, F. ; Lelieveldt, B.P.F. ; Boudraa, A. ; Janier, M.F. ; Revel, D. ; Reiber, J.H.C.

  • Author_Institution
    Dept. of Radiol., Leiden Univ., Netherlands
  • Volume
    20
  • Issue
    12
  • fYear
    2001
  • Firstpage
    1302
  • Lastpage
    1313
  • Abstract
    This paper describes a multimodality framework for computer-aided myocardial viability assessment based on neurofuzzy techniques. The proposed approach distinguishes two main levels: the modality-independent inference level and the modality-dependent application level. This two-level distinction releases the hard constraint of multimodality image registration. An abstract description template is used to describe the different myocardial functions (contractile function, perfusion, metabolism). Parameters extracted from different image modalities are combined to derive a diagnostic image. The neuro-fuzzy techniques make our system transparent, adaptive and easily extendable. Its effectiveness and robustness are demonstrated in a positron emission tomography/magnetic resonance imaging data fusion application.
  • Keywords
    biomedical MRI; cardiology; fuzzy neural nets; medical image processing; muscle; parameter estimation; positron emission tomography; sensor fusion; PET; abstract description template; computer-aided myocardial viability assessment; contractile function; diagnostic image; medical diagnostic imaging; neuro-fuzzy systems; parameters extraction; positron emission tomography/magnetic resonance imaging data fusion; two-level distinction; Adaptive systems; Application software; Biochemistry; Data mining; Fuzzy neural networks; Image registration; Magnetic resonance imaging; Myocardium; Positron emission tomography; Robustness; Artificial Intelligence; Cell Survival; Fluorodeoxyglucose F18; Fuzzy Logic; Heart; Humans; Image Interpretation, Computer-Assisted; Magnetic Resonance Imaging; Myocardial Infarction; Myocardium; Neural Networks (Computer); Tomography, Emission-Computed;
  • fLanguage
    English
  • Journal_Title
    Medical Imaging, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0278-0062
  • Type

    jour

  • DOI
    10.1109/42.974925
  • Filename
    974925